Simon,
Thanks!
I changed in Cython to
def primes_list(int kmax):
cdef int k, i
cdef long long n
cdef long long p[20000]
and now I am getting 2.1 seconds - exactly the same time as Julia and Java
with longs...
Since the computational difference between 64bit longs and 32bit ints is
soo high - is there any way to rewrite my toy example to force Julia to do
32 bit int calculations?
All best,
Przemyslaw Szufel
On Tuesday, 14 January 2014 23:55:12 UTC+1, Simon Kornblith wrote:
>
> In C long is only guaranteed to be at least 32 bits (IIRC it's 64 bits on
> 64-bit *nix but 32-bit on 64-bit Windows). long long is guaranteed to be
> at least 64 bits (and is 64 bits on all systems I know of).
>
> Simon
>
> On Tuesday, January 14, 2014 5:46:04 PM UTC-5, Przemyslaw Szufel wrote:
>>
>> Simon,
>> Thanks for the explanation!
>> In Java int is 32 bit as well.
>> I have just replaced ints with longs in Java and found out that now I get
>> the Java speed also very similar to Julia.
>>
>> However I tried in Cython:
>> def primes_list(int kmax):
>> cdef int k, i
>> cdef long n
>> cdef long p[20000]
>> ...
>>
>> and surprisingly the speed did not change...at first I thought that maybe
>> something did not compile or is in cache - but I made sure - it's not the
>> cache.
>> Cython speed remains unchanged regardles using int or long?
>> I know that now it becomes other language question...but maybe someone
>> can explain?
>>
>> All best,
>> Przemyslaw Szufel
>>
>>
>> On Tuesday, 14 January 2014 23:29:40 UTC+1, Simon Kornblith wrote:
>>>
>>> With a 64-bit build, Julia integers are 64-bit unless otherwise
>>> specified. In C, you use ints, which are 32-bit. Changing them to long long
>>> makes the C code perform similarly to the Julia code on my system.
>>> Unfortunately, it's hard to operate on 32-bit integers in Julia, since +
>>> promotes to 64-bit by default (am I missing something)?
>>>
>>> Simon
>>>
>>> On Tuesday, January 14, 2014 4:32:16 PM UTC-5, Przemyslaw Szufel wrote:
>>>>
>>>> Dear Julia users,
>>>>
>>>> I am considering using Julia for computational projects.
>>>> As a first to get a feeling of the new language a I tried to benchmark
>>>> Julia speed against other popular languages.
>>>> I used an example code from the Cython tutorial:
>>>> http://docs.cython.org/src/tutorial/cython_tutorial.html [ the code
>>>> for finding n first prime numbers].
>>>>
>>>> Rewriting the code in different languages and measuring the times on my
>>>> Windows laptop gave me the following results:
>>>>
>>>> Language | Time in seconds (less=better)
>>>>
>>>> Python: 65.5
>>>> Cython (with MinGW): 0.82
>>>> Java : 0.64
>>>> Java (with -server option) : 0.64
>>>> C (with MinGW): 0.64
>>>> Julia (0.2): 2.1
>>>> Julia (0.3 nightly build): 2.1
>>>>
>>>> All the codes for my experiments are attached to this post (Cython i
>>>> Python are both being run starting from the prim.py file)
>>>>
>>>> The thing that worries me is that Julia takes much much longer than
>>>> Cython ,,,
>>>> I am a beginner to Julia and would like to kindly ask what am I doing
>>>> wrong with my code.
>>>> I start Julia console and use the command include ("prime.jl") to
>>>> execute it.
>>>>
>>>> This code looks very simple and I think the compiler should be able to
>>>> optimise it to at least the speed of Cython?
>>>> Maybe I my code has been written in non-Julia style way and the
>>>> compiler has problems with it?
>>>>
>>>> I will be grateful for any answers or comments.
>>>>
>>>> Best regards,
>>>> Przemyslaw Szufel
>>>>
>>>
